Highly effective cancer drugs, such as doxorubicin and trastuzumab (Herceptin) are used widely in the treatment of many cancers and have led to important survival gains. However, these agents carry a significant risk of cardiovascular (CV) morbidity and mortality in a growing cancer population of over 12.7 million individuals worldwide. Doxorubicin-induced cardiotoxicity occurs in 9% of treated patients at dosages of 250mg/m2, and carries a particularly poor prognosis once it ensues. The combination of doxorubicin and trastuzumab result in an increased incidence of cardiotoxicity of 18-34% and severe heart failure in 2-4%. The objective of this proposal is to develop multimarker risk prediction algorithms which comprehensively integrate key biologic, imaging, and clinical data to identify patients at increased risk for doxorubicin- and doxorubicin + trastuzumab-induced cardiotoxicity. In Aim 1, we will determine if the level of or interval change in multiple biomarkers is associated with the risk of cardiotoxicity in participants from the Penn Cardiotoxicity of Cancer Therapy (CCT) cohort, an established longitudinal prospective cohort study of breast cancer patients undergoing treatment with doxorubicin or doxorubicin + trastuzumab. In Aim 2, we will determine if baseline or early changes in sensitive echocardiographic measures of cardiac function and myocardial mechanics are associated with the risk of cardiotoxicity in this cohort. We will leverage this new knowledge and integrate these findings in Aim 3, and develop risk prediction algorithms to identify individual patients at increased risk for doxorubicin and doxorubicin + trastuzumab-induced cardiotoxicity. We will derive these scores in the Penn CCT cohort, and externally validate our findings in the Vanderbilt (VUMC) Doxorubicin cohort and Massachusetts General Hospital (MGH) Herceptin cohorts. All analyses, including our risk scores, will be stratified by treatment regimen (doxorubicin alone and doxorubicin + trastuzumab). Through this comprehensive proposal, we will define the utility of an integrated multimarker approach in predicting cancer therapy cardiotoxicity. By improving the CV risk stratification of individual patients, we will help ensure the safe delivery of highly effective an necessary cancer therapies; enable the early institution of cardioprotective strategies; prevent the interruption or discontinuation of cancer therapy; and reduce early and late CV and oncologic morbidity and mortality. This work will advance our biologic and physiologic understanding of this disease and accelerate the discovery of strategies to help prevent and treat cancer therapy cardiotoxicity.